Work

Multioutput least square SVR-based multivariate EWMA control chart: The performance evaluation and application

Year: 2018

Type: article

Abstract: Autocorrelation leads to a bias estimator of standard control charts. It is important to develop control chart that allows autocorrelation and to evaluate its performance. The objective of this paper is to evaluate the performance of multioutput least square support vector regression (MLS-SVR)-based multivariate exponentially weighted moving average (MEWMA) control chart for monitoring multivariate autocorrelated data. For first order of vector autoregressive (VAR) and first order of vector moving average data, the proposed control chart tends to yield stable in-control average run length at about 200. The proposed control chart becomes more insensitive due to the increase of MEWMA smoothing parameter. In the real application, the proposed method is successfully applied to monitor water turbidity and chlorine residual data in the drinking water manufacturing process.

Source: Cogent Engineering

DOI: 10.1080/23311916.2018.1531456

Authors: Hidayatul Khusna, Muhammad Mashuri, Suhartono Suhartono, Dedy Dwi Prastyo, Muhammad Ahsan

Institution: Institut Teknologi Sepuluh Nopember

Language: English

Topic: Advanced Statistical Process Monitoring

Subfield: Statistics, Probability and Uncertainty

Field: Decision Sciences

Domain: Social Sciences

Open Access status: gold

Estimated APC paid: $1,165

Funder: Institut Teknologi Sepuluh Nopember